853 resultados para Knowledge Management Maturity Model


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This paper explores the micro-level processes of interaction across organisational boundaries and occupational communities. Based on a retrospective processual analysis, this study shows that in filling knowledge gaps, organisations put in place a series of knowledge mechanisms, which lead them to socially interact with their alliance partners. Both the deployment of existing knowledge and the creation of new knowledge are based on processes of interaction, which derive from the interplay between alliance actors. It is suggested that through both social interaction and the use of boundary objects, individuals are able to communicate, engage in problem-solving activities and share their ideas to fill knowledge gaps.

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A number of professional sectors have recently moved away from their longstanding career model of up-or-out promotion and embraced innovative alternatives. Professional labor is a critical resource in professional service firms. Therefore, changes to these internal labor markets are likely to trigger other innovations, for example in knowledge management, incentive schemes and team composition. In this chapter we look at how new career models affect the core organizing model of professional firms and, in turn, their capacity for and processes of innovation. We consider how professional firms link the development of human capital and the division of professional labor to distinctive demands for innovation and how novel career systems help them respond to these demands.

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We propose that strategic human resource management (SHRM) practices nurture a context of knowledge sharing where tacit knowledge can be turned into explicit knowledge and that this type of knowledge sharing promotes innovative behaviours. We draw on the fields of knowledge management and international human resource management to show why organisations need to turn tacit knowledge into explicit knowledge to gain most from their workforce skills and creativity. Findings from a couple of cross-national case studies show how SHRM promotes employees to interact and share knowledge so that there is a conversion of tacit knowledge to explicit knowledge that informs innovative behaviour. In Case Study 1, the focus is on a UK local authority that implemented a bundle of SHRM practices through a people management programme, which resulted in a flattened management structure. In Case Study 2, the focus is on a geriatric hospital in Malta that introduced a management presence to an interdisciplinary team working to improve patient care. The analysis also highlights the methodological contribution of qualitative research for enabling inductive enquiry that yields emergent themes - an approach not typically seen in SHRM innovation studies. © 2013 Taylor & Francis.

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Procedural knowledge is the knowledge required to perform certain tasks. It forms an important part of expertise, and is crucial for learning new tasks. This paper summarises existing work on procedural knowledge acquisition, and identifies two major challenges that remain to be solved in this field; namely, automating the acquisition process to tackle bottleneck in the formalization of procedural knowledge, and enabling machine understanding and manipulation of procedural knowledge. It is believed that recent advances in information extraction techniques can be applied compose a comprehensive solution to address these challenges. We identify specific tasks required to achieve the goal, and present detailed analyses of new research challenges and opportunities. It is expected that these analyses will interest researchers of various knowledge management tasks, particularly knowledge acquisition and capture.

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In this demonstration, we will present a semantic environment called the K-Box. The K-Box supports the lightweight integration of knowledge tools, with a focus on semantic tools, but with the flexibility to integrate natural language and conventional tools. We discuss the implementation of the framework, and two existing applications, including details of a new application for developers of semantic workflows. The demonstration will be of interest to developers and researchers of ontology-based knowledge management systems, and semantic desktops, and to analysts working with cross-media information. © 2011 ACM.

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Despite years of effort in building organisational taxonomies, the potential of ontologies to support knowledge management in complex technical domains is under-exploited. The authors of this chapter present an approach to using rich domain ontologies to support sense-making tasks associated with resolving mechanical issues. Using Semantic Web technologies, the authors have built a framework and a suite of tools which support the whole semantic knowledge lifecycle. These are presented by describing the process of issue resolution for a simulated investigation concerning failure of bicycle brakes. Foci of the work have included ensuring that semantic tasks fit in with users’ everyday tasks, to achieve user acceptability and support the flexibility required by communities of practice with differing local sub-domains, tasks, and terminology.

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In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised machine learning method called CORDER (COmmunity Relation Discovery by named Entity Recognition) to turn these unstructured data into structured information for knowledge management in these organizations. CORDER exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments in an expert evaluation, a quantitative benchmarking, and an application of CORDER in a social networking tool called BuddyFinder.

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A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

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Purpose – This paper describes a “work in progress” research project being carried out with a public health care provider in the UK, a large NHS hospital Trust. Enhanced engagement with patients is one of the Trust’s core principles, but it is recognised that much more needs to be done to achieve this, and that ICT systems may be able to provide some support. The project is intended to find ways to better capture and evaluate the “voice of the patient” in order to lead to improvements in health care quality, safety and effectiveness. Design/methodology/approach – We propose to investigate the use of a patient-orientated knowledge management system (KMS) in managing knowledge about and from patients. The study is a mixed methods (quantitative and qualitative) investigation based on traditional action research, intended to answer the following three research questions: (1) How can a KMS be used as a mechanism to capture and evaluate patient experiences to provoke patient service change (2) How can the KMS assist in providing a mechanism for systematising patient engagement? (3) How can patient feedback be used to stimulate improvements in care, quality and safety? Originality/value –This methodology aims to involve patients at all phases of the study from its initial design onwards, thus leading to an understanding of the issues associated with using a KMS to manage knowledge about and for patients that is driven by the patients themselves. Practical implications – The outcomes of the project for the collaborating hospital will be firstly, a system for capturing and evaluating knowledge about and from patients, and then as a consequence, improved outcomes for both the patients and the service provider. More generally, it will produce a set of guidelines for managing patient knowledge in an NHS hospital that have been tested in one case example.

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The value of knowing about data availability and system accessibility is analyzed through theoretical models of Information Economics. When a user places an inquiry for information, it is important for the user to learn whether the system is not accessible or the data is not available, rather than not have any response. In reality, various outcomes can be provided by the system: nothing will be displayed to the user (e.g., a traffic light that does not operate, a browser that keeps browsing, a telephone that does not answer); a random noise will be displayed (e.g., a traffic light that displays random signals, a browser that provides disorderly results, an automatic voice message that does not clarify the situation); a special signal indicating that the system is not operating (e.g., a blinking amber indicating that the traffic light is down, a browser responding that the site is unavailable, a voice message regretting to tell that the service is not available). This article develops a model to assess the value of the information for the user in such situations by employing the information structure model prevailing in Information Economics. Examples related to data accessibility in centralized and in distributed systems are provided for illustration.

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This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

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* Under Knowledge Infrastructure we imply all the means that enable effective knowledge management within organization ~ knowledge process support.

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The advances in building learning technology now have to emphasize on the aspect of the individual learning besides the popular focus on the technology per se. Unlike the common research where a great deal has been on finding ways to build, manage, classify, categorize and search knowledge on the server, there is an interest in our work to look at the knowledge development at the individual’s learning. We build the technology that resides behind the knowledge sharing platform where learning and sharing activities of an individual take place. The system that we built, KFTGA (Knowledge Flow Tracer and Growth Analyzer), demonstrates the capability of identifying the topics and subjects that an individual is engaged with during the knowledge sharing session and measuring the knowledge growth of the individual learning on a specific subject on a given time space.

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The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.

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The major contribution of the study is the identification of a positive link between perceived effective managerial coaching (PEMC) and team task performance and also, the examination of PEMC adopting a multilevel research design and incorporating dual-source data. Specifically, drawing on social psychology, the thesis aims at developing and testing a comprehensive conceptual framework of the antecedents and consequences of PEMC for knowledge workers. The model takes into consideration intrapersonal, interpersonal and team-level characteristics, which relate to PEMC and, subsequently associate with important work outcomes. In this regard, the thesis identifies PEMC as a practice of dual nature in that it may be experienced not only as a one-on-one workplace developmental interaction, but also as a managerial practice that is experienced by each member of a team for co-ordination purposes. Adopting a cross-sectional survey research design, the hypotheses are tested in three organisations in Greece and the UK. In particular, hierarchical linear modelling of 191 employees nested in 60 teams yields that employees’ learning goal orientation (LGO) and high-quality exchanges between an employee and a manager (LMX) are positively related to effective MC, while a manager’s LGO moderates the relationship between employees’ LGO and PEMC. In turn, PEMC, as a one-on-one practice, is related to cognitive outcomes, such as information sharing, while as a shared team practice is related also to behavioural outcomes, including individual and team performance. Overall, the study contributes to a growing body of coaching and management literature that acknowledges PEMC as a core managerial practice.